CN113186311A

CN113186311A - Application of vaginal microorganism in differential diagnosis of chronic pelvic pain syndrome

Info

Publication number: CN113186311A
Application number: CN202110458431.2A
Authority: CN
Inventors: 王姝; 钞晓培; 刘阳; 郎景和
Original assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Current assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Priority date: 2021-04-27
Filing date: 2021-04-27
Publication date: 2021-07-30
Anticipated expiration: 2041-04-27
Also published as: CN113186311B

Abstract

The invention relates to the technical field of biology, in particular to application of vaginal microorganisms in differential diagnosis of Chronic Pelvic Pain Syndrome (CPPS). The invention provides application of a reagent for detecting the content of a biomarker of chronic pelvic pain syndrome in preparation of a product for identifying chronic pelvic pain syndrome. The invention provides a group of Endometriosis (EM)/Adenomyosis (AM) related CPP biomarkers, namely Clostridium diplocarum, Lactobacillus reuteri and/or CA125, which can be used for early diagnosis and differential diagnosis of EM/AM related CPP, have good detection specificity and high sensitivity, and are used for identifying and guiding clinical treatment of EM/AM related CPP patients, so that the patients can obtain better treatment effect from treatment.

Description

Application of vaginal microorganism in differential diagnosis of chronic pelvic pain syndrome

Technical Field

The invention relates to the technical field of biology, in particular to application of vaginal microorganisms in differential diagnosis of chronic pelvic pain syndrome.

Background

Chronic Pelvic Pain Syndrome (CPPS) is one of the common Pain problems in women, associated with a variety of gynaecological disorders, defined as intermittent or continuous Pain in the lower abdomen or Pelvic cavity lasting at least 6 months. CPP is a complaint of patients accounting for 2-10% of all gynecological visits, of which about 20% have undergone laparoscopic exploratory surgery and 10-15% have undergone hysterectomy. However, the knowledge of CPP is still poor and the diagnosis of CPP is difficult.

CPPS is a multifactorial syndrome with diverse etiologies and contains underlying causative factors including infection, inflammation, and other key factors. According to the study of royal gynecology academy of obstetrics (RCOG), the causes of pain can be divided into gynecological and non-gynecological factors. The former includes endometriosis/adenomyosis (EM/AM), pelvic congestion syndrome, leiomyoma, malignant disease, pelvic inflammation, adhesion, etc. There are currently definite effective treatment regimens for AM and EM, but they do not provide effective non-surgical treatment for such patients when diagnosis is unknown. If the EM/AM related CPP can be identified from CPP patients caused by other causes, the EM/AM related CPP patients can be more effectively treated, the clinical symptoms of the patients can be fully relieved, and the life quality of the patients can be improved. Current diagnosis of EM and AM relies primarily on imaging examinations, including B-mode ultrasound and Magnetic Resonance Imaging (MRI). In the diagnosis of AM, the sensitivity of B-mode ultrasound diagnosis is 75% -88%, the specificity is 67% -93%, while the MRI accuracy is 85% -95%, and the specificity is 67% -99%. MRI is limited in clinical use due to its high cost. In addition, it is noted that B-mode ultrasound and MRI are mostly in the late stage of the disease when diagnosing AM and EM, and early diagnosis and early treatment cannot be achieved.

With the development of microbiology and understanding of the role of microorganisms in disease, researchers have come to appreciate the value of microorganisms as potential biomarkers for disease diagnosis. Currently, there are no validated biomarkers that can distinguish EM/AM-associated CPPs from CPPS caused by other diseases. Ambiguous diagnoses do not allow such patients to receive more targeted and effective non-surgical treatment. Therefore, more accurate and noninvasive biomarkers should be explored, the differential diagnosis of EM/AM related CPP in clinic is realized, and a basis is provided for a more targeted treatment scheme of a clinician.

Disclosure of Invention

In view of the above problems, it is an object of the present invention to provide a biomarker for early diagnosis and/or differential diagnosis of EM/AM-induced CPP, and to elucidate its clinical application value.

The invention also aims to provide a microorganism detection kit which has high sensitivity, simple operation and noninvasive and rapid speed and is used for identifying and guiding clinical treatment of EM/AM related CPP patients.

In order to achieve the purpose, the specific technical scheme of the invention is as follows:

in a first aspect, the invention provides a use of a reagent for detecting the content of a biomarker of chronic pelvic pain syndrome in the preparation of a diagnostic product of chronic pelvic pain syndrome, wherein the biomarker is selected from one or more of the following microbial markers in combination: alloscardovia _ omnicolens, Clostridium _ disporicum, Lactobacillus _ jensenii, Lactobacillus _ reuteri, Lactobacillus _ iners, Lactobacillus _ monotpelliensis, Clostridium _ butyricum.

Preferably, the diagnosis comprises differential diagnosis and/or early diagnosis.

Preferably, the chronic pelvic pain syndrome includes EM/AM-associated CPP and CPP caused by other diseases.

In some embodiments of the invention, the differential diagnostic microbial markers are Clostridium _ disporicum and Lactobacillus _ reuteri.

Preferably, the differential diagnostic biomarker further comprises the serum marker CA 125.

In some embodiments of the invention, the method for determining the content of the microbial marker comprises 16S sequencing or qPCR quantitative detection;

the microbial marker content is determined by amplifying a fragment of each of the microbial markers in the subject sample; preferably, the fragment is a fragment of a 16S ribosomal nucleic acid gene.

The determination method of the serum marker content comprises an immunoassay method, such as a chemiluminescence micro-particle immunoassay method (CMIA).

Preferably, the test sample is a vaginal secretion and/or serum sample.

In a second aspect, the present invention provides a microbiological kit for differential diagnosis of EM/AM-related CPP, comprising reagents for detecting the levels of Clostridium _ disporicum and Lactobacillus _ reuteri.

In some embodiments of the invention, when the kit detects a relative abundance of Clostridium diploricum in a sample that is more than 0.001105% and a relative abundance of Lactobacillus reuteri in a sample that is less than 0.1911349%, the sample is diagnosed as positive for EM/AM-associated CPP.

In a third aspect, the present invention provides a microbial kit for differential diagnosis of EM/AM-related CPP, which comprises reagents for detecting the levels of Clostridium _ disporicum, Lactobacillus _ reuteri and CA 125.

In some embodiments of the invention, when the kit detects a relative abundance of Clostridium disporicum in a sample above 0.001105%, while a relative abundance of Lactobacillus reuteri is below 0.1911349%, and serum CA125 solubility exceeds 35U/mL, the sample is diagnosed as positive for EM/AM-associated CPP.

In a fourth aspect, the invention provides the use of the microbial markers Clostridium _ disporicum, Lactobacillus _ reuteri and/or serum marker CA125 in the construction of a model for predicting the risk of EM/AM-associated CPP.

Preferably, the input variables of the risk model are the content of the microbial and serum markers.

Based on the technical scheme, the invention has the following beneficial effects:

the invention provides a group of biomarkers of EM/AM related CPP, namely Clostridium diplocarum, Lactobacillus reuteri and/or CA125, which can be used for early diagnosis and differential diagnosis of EM/AM related CPP and have good detection specificity and high sensitivity.

The invention provides a microorganism detection kit which has high sensitivity, simple operation and non-invasive and rapid speed, and the kit comprises a Clostridium disporicum and Lactobacillus reuteri content detection reagent and is used for identifying and guiding clinical treatment of EM/AM related CPP patients. In the training set, the sensitivity of the kit was 81.1% and the specificity was 52.0%. The sensitivity of the CA125 diagnosis was 40.5% and the specificity was 100%. When the kit was combined with CA125, the sensitivity of the diagnosis increased to 89.2%. In the validation set, the sensitivity of the kit for diagnosing EM/AM related CPP is 70.0%, and the specificity is 53.6%. The sensitivity of the CA125 diagnosis was 46% and the specificity was 100%. When the two are combined, the sensitivity is as high as 86.0%.

Drawings

FIG. 1 the composition of the community of vaginal bacteria. (a) Histogram of flora with phylum level ranked top 10 relative abundance. (b) Genus level histogram ranking top 10 relative abundance of flora. (c) Genus level histogram of flora ranked 30 top relative abundance. (d) Histogram of flora with species level relative abundance ranking top 10.

Figure 2a diversity analysis. (a) Dilution curves for vaginal microbiome diversity, error bars represent standard deviations. The α diversity analysis showed the species differences observed within the three groups, group a: total 626, group B: total 409 species, group C: in total 465. (b) Histogram of microbial community diversity.

Figure 3 vaginal microbiota composition. (a) A weighted average based uniforac distance matrix heat map showing the differences between groups between the three groups. The numbers in the figure are the difference coefficients between two samples. The smaller the coefficient of variation, the smaller the variation in the diversity of the microbiome. (b) Histogram of differences between vaginal microbial species based on Anosim analysis. (c) The differences in abundance at the genus level among the groups were significantly analyzed based on MetaStat. (d) The differences in genus and species level abundances were significant in the various groups based on t-test analysis. (e) LEfSe analysis was performed on the vaginal microbiota of three groups of patients. LEfSe can identify species events that differ significantly between groups. All of the graphs had statistical significance (P <0.05), and LDA scores > + -4,. Prefixes represent abbreviations for the classification level of each taxon: door (p _), category (c _), order (o _), family (f _), genus (g _), and category (s _).

Detailed Description

The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention. Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art.

The experimental procedures used in the following examples are all conventional procedures unless otherwise specified.

All materials, reagents and the like in the following examples are commercially available unless otherwise specified.

Example 1 screening for microbial markers associated with EM/AM-associated chronic pelvic pain

1. Study object

Patients who were enrolled in a concurrent gynecological surgery with CPPS patients attending a gynecological clinic at the department of obstetrics and gynecology in the department of beijing in conjunction with a hospital in 2017 to 2018, 12 months.

Inclusion criteria were: premenopausal women during non-menstrual, non-pregnant, non-puerperium periods were included. Among all patients in the group, 37 cases of CPPS, which were confirmed to be EM/AM by laparoscopic exploration or surgical pathology, were defined as group A. 25 CPPS patients with pelvic adhesions, hydrosalpinx or infertility via laparoscopic probing were defined as group B. 66 patients without CPPS were included as normal controls (most of which received routine examination or pre-pregnancy counseling), defined as group C. Cervical Human Papilloma Virus (HPV) detection was negative for all participants.

Exclusion criteria were as follows: (I) asexual life women; (II) a postmenopausal woman; (III) cervical HPV infection, fever (>37.5 ℃) or women with a history of malignant disease; (IV) women diagnosed with acute lower genital tract inflammation or lower urinary or digestive tract disease; (V) women with autoimmune disease or diabetes. Furthermore, all participants should also meet the following requirements: no systemic antibiotics or antifungal medicines or vaginal suppository is used within 14 days before sampling; no room was taken within 3 days prior to sampling, or no vaginal douches were taken within 2 days prior to sampling.

2. Specimen collection

The specimen is collected when the patient first visits the clinic. Fully exposing vagina and cervix with disposable lubricant-free sterile speculum, and removing vaginal fornix with sterile swabHoleVaginal secretions were obtained. The sterile swab samples were immediately stored in a-80 ℃ refrigerator for subsequent DNA extraction. Samples of TCT and HPV were collected simultaneously for detection.

3. 16S rRNA sequencing

3.1 extraction and PCR amplification of genomic DNA

Extracting the genomic DNA of the sample by an SDS method, detecting the purity and the concentration of the DNA by agarose gel electrophoresis, taking a proper amount of the sample DNA in a centrifugal tube, and diluting the sample to 1 ng/mu l by using sterile water.

Using diluted genomic DNA as a template, specific primers with Barcode, New England Biolabs, were used according to the selection of the sequencing region

And carrying out PCR by using a High-Fidelity PCR Master Mix with GC Buffer and High-efficiency and High-Fidelity enzyme to ensure the amplification efficiency and accuracy.

Primer corresponding region:

primers for region 16S V4 (515F and 806R): identifying bacterial diversity;

3.2 mixing and purification of PCR products

The PCR product is detected by electrophoresis by using agarose gel with 2 percent concentration; and (3) carrying out equal-quantity sample mixing according to the concentration of the PCR product, fully and uniformly mixing, detecting the PCR product by using 2% agarose gel electrophoresis, and recovering the product from the target band by using a gel recovery kit provided by qiagen company.

3.3 library construction and on-machine sequencing

Use of

And (3) constructing a library by using a DNA PCR-Free Sample Preparation Kit, quantifying the constructed library by using the Qubit and Q-PCR, and performing on-machine sequencing by using Hiseq2500 after the library is qualified. The sequencing experiments were performed by the Beijing Nonozao Source company.

4. Data analysis

For clinical data analysis, SPSS 23.0 software (SPSS inc., Chicago, IL, USA) was used. The continuous variable conforming to normal distribution adopts t test, and the classified variable adopts chi-square test. Statistical differences were considered when P < 0.05.

4.1 sequencing data processing

Splitting each sample data from off-line data according to a Barcode sequence and a PCR amplification primer sequence, splicing reads of each sample by using FLASH (V1.2.7, http:// ccb. jhu. edu/software/FLASH /) after the Barcode and the primer sequence are cut off, and obtaining a spliced sequence which is original Tags data (Raw Tags); the Raw Tags obtained by splicing need to be strictly filtered to obtain high-quality tag data (Clean Tags). With reference to the Tags quality control scheme for Qiime (V1.9.1, http:// Qiime. org/scripts/split _ library _ fastq. html), the following operations were performed: a) and (5) intercepting Tags: truncating Raw Tags from the first low-quality base site of consecutive low-quality values (default quality threshold of 19) base numbers to a set length (default length value of 3); b) tags length filtration: and (3) further filtering the Tags data set obtained by intercepting the Tags, wherein the length of the continuous high-quality base is less than 75% of the length of the Tags. The Tags obtained after the treatment needs to be subjected to chimera sequence removal treatment, the Tags sequence is compared with a species annotation database to detect a chimera sequence, and the chimera sequence is finally removed to obtain the final Effective data (Effective Tags).

4.2OTU clustering and species Annotation

All Effective Tags of all samples are clustered by using Upearse algorithm (Upearse v7.0.1001, http:// www.drive5.com/Uparse /), sequences are clustered into OTUs (operational taxomic units) by default with 97% consistency (Identity), and meanwhile, representative sequences of the OTUs are selected, and the sequences with the highest occurrence frequency in the OTUs are selected as the representative sequences of the OTUs according to the algorithm principle. Species annotation was performed on OTUs sequences, species annotation analysis was performed using the Mothur method with the SSUrRNA database of SILVA132(http:// www.arb-SILVA. de /) (setting threshold values of 0.8-1), and taxonomic information was obtained and used at each taxonomic level: kingdom, phylum, class, order, family, genus, species, and statistics of community composition for each sample. Rapid multiple sequence alignment was performed using MUSCLE (Version 3.8.31, http:// www.drive5.com/MUSCLE /) software to obtain phylogenetic relationships for all OTUs representative sequences. And finally, carrying out homogenization treatment on the data of each sample by taking the data with the minimum data amount in the sample as a standard, wherein the subsequent Alpha diversity analysis and Beta diversity analysis are based on the data after the homogenization treatment.

4.3 sample complexity analysis (Alpha Diversity)

Calculating the indexes of observer-otus, Chao1, Shannon, Simpson, ace, Goods-coverage, PD _ whole _ tree using Qiime software (Version 1.9.1), drawing a dilution curve using R software (Version 2.15.3), a Rank absendance curve, a species accumulation curve and performing inter-group variance analysis using R software for Alpha diversity index; differential analysis between Alpha diversity index groups will be performed with parametric and non-parametric tests, respectively, with T-test and wilcoxo tests being selected if there are only two groups, and Tukey test and wilcoxo test of agricolae package being selected if there are more than two groups.

The Alpha diversity index is specifically described as follows:

the indices for calculating the abundance (Community richness) of a flora are:

Chao-the Chao1 estimator

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.chao1.html#skbio.diversity.alpha.chao1)；

ACE-the ACE estimator

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.ace.html#skbio.diversity.alpha.ace)；

the indices for calculating the diversity of the flora (Community diversity) are:

Shannon-the Shannon index

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.shannon.html#skbio.diversity.alpha.shannon)；

Simpson-the Simpson index

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.simpson.html#skbio.diversity.alpha.simpson)；

the sequencing depth index is as follows:

Coverage-the Good’s coverage

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.goods_coverage.html#skbio.diversity.alpha.goods_coverage)；

indices of phylogenetic diversity are:

PD_whole_tree-PD_whole_tree index

(http://scikit-bio.org/docs/latest/generated/skbio.diversity.alpha.faith_pd.htmlhighlight＝pd#skbio.diversity.alpha.faith_pd)

4.4 multiple sample comparison analysis (Beta Diversity)

The distance of Unifrac is calculated by Qiime software (Version 1.9.1) to construct UPGMA sample cluster tree. Plots of PCA, PCoA and NMDS were made using R software (Version 2.15.3). PCA analysis uses ade4 package and ggplot2 package of R software, PCoA analysis uses WGCNA, stats and ggplot2 package of R software, and NMDS analysis uses vegan package of R software. And (3) performing difference analysis between Beta diversity index groups by using R software, and performing parametric test and non-parametric test respectively, wherein T-test and wilcoxo test are selected if only two groups exist, and Tukey test and wilcoxo test of agricolae package are selected if more than two groups exist.

LEfSe analysis used LEfSe software to default to a screening value of 4 for LDA Score. Metastats analysis uses R software to perform persistence test between groups at various classification levels (Phylum, Class, Order, Family, Genus, specifices) to obtain p-values, and then corrects the p-values by the Benjamini and Hochberg face Discovery Rate method to obtain q-values. The anosims, MRPP and Adonis analyses used the anosims function, MRPP function and Adonis function of the R vegan package, respectively. The AMOVA analysis uses the mothur software AMOVA function. Species analysis with significant differences between groups T _ test between groups was performed using R software and plotted.

5. Results

5.1 statistics of clinical information

The mean age of group a was 39.89 ± 6.24 years, 37.56 ± 5.48 for group B, 38.23 ± 7.80 for group C, and there was no significant difference between the three groups (P ═ 0.368). In addition, there were no significant differences in pregnancy, parity, menstrual period, contraceptive method (P values of 0.077, 0.191, 0.270 and 0.216, respectively) among the three groups. Table 1 shows the clinical information profile of three groups of patients.

TABLE 1 patient demographics

The abbreviation is: IUD, intrauterine device; SD, standard deviation.

Note that: the P value is calculated using the chi-square and t-test.

5.2 microbial community diversity

(1) Identification of vaginal microbiota

In the present invention, 57 gates, 1017 genera and 919 species were detected in total. The distribution of vaginal bacteria at different levels is shown in figure 1.

(2) Structure of vaginal microbiome in group 3

The alpha-diversity of the OTU of the microorganisms in group 3 was determined from the samples. As can be seen in FIG. 2a, the microbial species diversity was highest in group A, followed by group C, and then group B. As can be seen from fig. 2B, based on the PD _ white _ tree analysis, the diversity of vaginal microbiota in group a was significantly higher than in group B or group C, but there was no significant difference between group B and group C (avs.b, P ═ 0.0278; a vs.c, P ═ 0.0430; B vs.c, P ═ 0.7396).

(3) Vaginal microbial composition distribution in group 3

Relative abundances were found in the top 30 genera by LEfSe algorithm, t-test analysis and MetaState analysis, with a significant difference in the relative abundance of a total of 26 species between groups a and B, with 3 being above 0.1%. The relative abundance of 36 species was significantly different between groups A and C, while the relative abundance of 6 was above 0.1%. A total of 22 species showed significant differences between group B and group C, with no species with relative abundances above 0.1% (Table 2) (FIG. 3C, 3d, 3 e).

As shown in table 2, the relative abundance of alloscarovia _ omniols, Clostridium _ disporicum was significantly increased, the relative abundance of Lactobacillus _ jenseniii was significantly decreased, and the difference was statistically significant (P < 0.05); compared with the group C, the relative abundance of Lactobacillus reuteri, Lactobacillus iners, Lactobacillus jensenii and Sneathia arnii is remarkably reduced, the relative abundance of Veillonella montpellierensis and Alloscardovia omnilensis is remarkably increased, and the difference has statistical significance (P < 0.05).

TABLE 2 statistics of genus and species differences between the first 30 genera among groups

Q value;^#the value of P;^&Kruskal-Wallis test P values.

When these three groups were analyzed together, it was found that the relative abundance of Lactobacillus jensenii was the lowest in group A, whereas Clostridium butyricum was significantly higher in group A (Table 3).

Statistics of genus and species differences among top 30 genera between Table 33 groups

In summary, through LEfSe, t test and MetaState analysis, at a species level with abundance within the first 30 genera, 7 species with significant differences were found in three groups, namely alloscarcavia _ omnicolens ℃, _ Clostridium _ disporicum ℃ @, Clostridium _ butyricum @, _ Veillonella _ montpelliensis @, Lactobacillus _ jensenii ↓, Lactobacillus _ inrs ↓, and Lactobacillus _ reuteri ↓.

Therefore, the 7 different species can be used as a microbial marker for early and/or differential diagnosis of chronic pelvic pain syndrome.

6. Diagnostic efficacy of vaginal microbiome

The inventors applied the ROC curve to determine the critical relative abundance of potential microbiome biomarkers to help distinguish EM/AM-related CPPs from other types in CPPs.

The inventor carries out single and double combination on the above-mentioned difference species to calculate the sensitivity and specificity of various combinations for identifying EM/AM related CPP patients, and as a result, the sensitivity and specificity are found as follows:

finally, it was found that when the relative abundance of Clostridium _ disporicum exceeds 0.001105% and that of Lactobacillus _ reuteri is below 0.1911349%, the differential diagnostic sensitivity and specificity for EM/AM-associated CPP were 81.1% and 52.0%, respectively. Further in combination with serum CA125 currently used clinically for the auxiliary diagnosis of AM and EM, it was found that when the microbial marker was combined with CA125, the sensitivity of the diagnosis was further increased to 89.2% (table 4, training set).

TABLE 4 comparison of different methods for diagnosing EM/AM-related CPPS

Method A means that the relative abundance of Clostridium disporicum is greater than 0.001105%, while the relative abundance of Lactobacillus reuteri is less than 0.1911349%; method B is that the solubility of serum CA125 exceeds 35U/mL; method C means that the relative abundance of Clostridium disporicum exceeds 0.001105%, the relative abundance of Lactobacillus reuteri is below 0.1911349%, and the serum CA125 solubility exceeds 35U/mL. SEN: sensitivity, SPE: specificity, PPN: positive predictive value, NPV: negative predictive value.

In summary, Clostridium _ butyricum, Clostridium _ disporicum, Alloscardovia _ omnicolens and Veillonella _ montpelliensis as the dominant bacterial group, while Lactobacillus _ jensenii, Lactobacillus _ reuteri and Lactobacillus _ iners are less abundant in relative amounts and may be associated with EM/AM-related CPP diseases or considered as potential pathogenic bacteria and potential biomarkers. When the inventor combines Clostridium _ Disporicum and Lactobacillus _ reuteri with serum CA125, the diagnosis effect of identifying EM/AM related CPP can be remarkably improved, the findings provide important data support for the etiology and the expression of EM/AM related CPP diseases, and provide a reliable biomarker development method for the differential diagnosis and even early diagnosis of EM/AM related CPP.

Example 2 validation of the correlation between the microbial markers of Clostridium disporicum and Lactobacillus reuteri and EM/AM-associated CPP

In the sample collection method of example 1, CPP patients were selected, swabs were left before surgery, and classified into 59 cases of "EM/AM-associated CPP group" and 16 cases of "other CPP group" based on the findings of surgical investigation and/or pathological diagnosis, and the relative concentration of the targeted microorganism was determined by 16S rRNA sequencing method. The patients were rated "yes" and "no" according to cut-off values defined in example 1, and then compared according to the gold standard diagnosis, thereby calculating sensitivity and specificity.

The detection result shows that the abundance level of Clostridium diplocarum is obviously increased, the abundance level of Lactobacillus reuteri is obviously reduced, and the difference has statistical significance (p < 0.05). The ROC curve results show that the diagnostic sensitivity and specificity of separating EM/AM related CPPs from CPPs were 70.00% and 53.62% when the relative abundance of Clostridium _ disporicum exceeded 0.001105% and Lactobacillus _ reuteri was less than 0.1911349%. Whereas the diagnostic sensitivity and specificity based on serum CA125 were 46% and 100.00%, respectively, when serum CA125 and vaginal biomarker were used in combination, the sensitivity increased to 86.00% (table 4, validation set).

The fact that Clostridium disporicum and Lactobacillus reuteri are used for differential diagnosis of EM/AM related CPP is suggested to have higher diagnostic efficacy.

Although the invention has been described in detail hereinabove with respect to a general description and specific embodiments thereof, it will be apparent to those skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.

Claims

1. Use of a reagent for detecting the content of a biomarker of chronic pelvic pain syndrome in the preparation of a diagnostic product of chronic pelvic pain syndrome, wherein the biomarker is selected from one or more of the following microbial markers in combination: alloscardovia _ omnicolens, Clostridium _ disporicum, Lactobacillus _ jensenii, Lactobacillus _ reuteri, Lactobacillus _ iners, Lactobacillus _ monotpelliensis, Clostridium _ butyricum.

2. Use according to claim 2, wherein the diagnosis comprises differential diagnosis and/or early diagnosis.

3. The use of claim 1, wherein the chronic pelvic pain syndrome comprises chronic pelvic pain caused by Endometriosis (EM)/Adenomyosis (AM) and chronic pelvic pain caused by other etiologies.

4. Use according to claim 3, wherein the differential diagnostic microbial markers are Clostridium _ disporicum and Lactobacillus _ reuteri.

5. The use of claim 4, wherein the differential diagnostic biomarker further comprises the serum marker CA 125.

6. The use according to claim 1, wherein the determination of the content of the microbial marker comprises any one or more of 16S sequencing or qPCR quantitative detection; the determination method of the serum marker content comprises an immunoassay method.

7. A microbiological kit for differential diagnosis of EM/AM-associated CPP, comprising reagents for detecting the levels of Clostridium _ disporicum and Lactobacillus _ reuteri.

8. The kit of claim 7, wherein the sample is diagnosed as positive for EM/AM-associated CPP when the kit detects a relative abundance of Clostridium disporicum above 0.001105% and a relative abundance of Lactobacillus reuteri below 0.1911349% in the sample.

9. A microbiological kit for differential diagnosis of EM/AM-associated CPP, comprising reagents for detecting the levels of Clostridium _ disporicum, Lactobacillus _ reuteri and CA 125.

10. The kit of claim 9, wherein the sample is diagnosed as positive for EM/AM-associated CPP when the kit detects a relative abundance of Clostridium disporicum in the sample of greater than 0.001105%, a relative abundance of Lactobacillus reuteri of less than 0.1911349%, and a serum CA125 solubility of greater than 35U/mL.